Web Browser Based Data Visualization Scheme for XBee Wireless Sensor Network

Authors

  • Xinzhou Wei Department of Electrical & Telecommunications Engineering Technology New York City College of Technology The City University of New York
  • Li Geng Department of Electrical and Telecommunications Engineering Technology, New York City College of Technology, City University of New York, 300 Jay St, Brooklyn, NY, U.S.A.
  • Xiaowen Zhang Department of Computer Science, College of Staten Island, City University of New York 2800 Victory Blvd., Staten Island, NY 10314, U.S.A.

DOI:

https://doi.org/10.14738/tnc.65.5261

Keywords:

Data visualization, Internet of Things, Smart building, Wireless sensor network, XBee, ZigBee.

Abstract

Wireless sensor network (WSN) plays an important role in the infrastructure of Internet of Things (IoT). Data visualization is an essential component in WSN to facilitate data scientists to interpret information clearly and efficiently.  In this paper, we conduct a study of XBee based WSN which integrates the DASH data visualization scheme for building a web-browser based application without using HTML or JavaScript. The data collected from wireless sensors in a WSN were displayed in a web browser with interactive functions. The proposed visualization scheme is real-time, cross platform, and hardware independent. Thus, it could be easily employed on any operating system. Experimental results demonstrated that our WSN data visualization scheme using XBee Python package and Plotly's DASH is feasible for IoT applications like smart buildings, environment monitoring, as well as other WSN applications.

Author Biographies

Xinzhou Wei, Department of Electrical & Telecommunications Engineering Technology New York City College of Technology The City University of New York

Xinzhou Wei is an Associate Professor in the Department of Electrical and Telecommunication Engineering Technology of the New York City College of Technology (CityTech) of The City University of New York (CUNY). He received his B.S. and M.S. degree from Xi'an Jiaotong University in 1988 and 1991 respectively. In 2002, he received his Ph.D. degree in Computer Science from the Graduate Center of CUNY. His research focuses on computer network security, telecommunication, and image processing. Currently he is an IEEE senior member and IEEE student branch faculty advisor at CityTech.

Li Geng, Department of Electrical and Telecommunications Engineering Technology, New York City College of Technology, City University of New York, 300 Jay St, Brooklyn, NY, U.S.A.

Li Geng is currently an Assistant Professor in Department of Electrical Engineering& Telecommunication Technology at New York City College of Technology of the City University of New York. She received her B. S. degree in Telecommunication Engineering from Huazhong University of Science and Technology, Wuhan, China, in 2009. She received her Ph.D. degree in Electrical Engineering from Stony Brook University, New York, USA, in 2015. Her research interests are in the area of statistical signal processing, signal detection and estimation, big data analytics, as well as their applications to a wide area such as indoor positioning in the Internet of Things.

Xiaowen Zhang, Department of Computer Science, College of Staten Island, City University of New York 2800 Victory Blvd., Staten Island, NY 10314, U.S.A.

Xiaowen Zhang is an Associate Professor in the Department of Computer Science at College of Staten Island and a doctoral faculty member in Ph.D. Program in Computer Science at CUNY Graduate Center. He received a Ph.D. in Computer Science from CUNY and a Ph.D. in Electrical Engineering from Beijing Jiaotong University. His research interests include information security, cryptography, quantum computing, wireless communications, biometrics, and RFID security and privacy. At CUNY Graduate Center, he has supervised three Ph.D. dissertations. He is currently supervising two Ph.D. students. He is a member of ACM and IEEE.

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Published

2018-11-04

How to Cite

Wei, X., Geng, L., & Zhang, X. (2018). Web Browser Based Data Visualization Scheme for XBee Wireless Sensor Network. Transactions on Networks and Communications, 6(5), 59. https://doi.org/10.14738/tnc.65.5261